Invention Grant
- Patent Title: Learning models for entity resolution using active learning
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Application No.: US15947166Application Date: 2018-04-06
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Publication No.: US11501111B2Publication Date: 2022-11-15
- Inventor: Kun Qian , Lucian Popa , Prithviraj Sen , Min Li
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Ryan, Mason & Lewis, LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N5/02 ; G06N20/00

Abstract:
Methods, systems, and computer program products for learning models for entity resolution using active learning are provided herein. A computer-implemented method includes determining a set of data items related to a task associated with structured knowledge base creation, and outputting the set of data items to a user for labeling. Such a method also includes generating, based on a user-labeled version of the set of data items, a candidate model for executing the task, and one or more generalized versions of the candidate model. Additionally, such a method can also include generating a final model based on one or more iterations of analysis of the candidate model and analysis of the one or more generalized versions of the candidate model, and performing the task by executing the final model on one or more datasets.
Public/Granted literature
- US20190311229A1 Learning Models For Entity Resolution Using Active Learning Public/Granted day:2019-10-10
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